Wireless communication systems are widely deployed to provide various communication services and location services to mobile users. Users in the system rely on position determination functionality to provide location services including navigation, location-based services, and point-of-interest applications.
A number of techniques exist to determine position of an access terminal in a wireless communication system, including Global Positioning System (GPS) techniques, Assisted GPS (A-GPS), and cell-based positioning methods such as Cell of Origin (COO), Time of Arrival (TOA), and Angle of Arrival (AOA). These techniques have varying degrees of precision, which may not provide the accuracy needed by many of today's location-based services. For example, GPS positioning can be especially inaccurate in urban environments, where tall, densely packed buildings can restrict views of satellites and the reflective surfaces of buildings can cause multipath effects.
One technique that improves on the accuracy of GPS in urban environments uses computer vision methods to determine position of access terminals equipped with cameras. These methods aim to solve a three-dimensional problem of finding extrinsic camera parameters (i.e., position and orientation) by minimizing the reprojection error between projections of object points and corresponding points identified on a camera image, e.g., using non-linear least squares minimization. A least squares approach can be optimized with iterative numerical methods, which are computationally expensive and cost prohibitive to implement in access terminals.